{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T16:46:54Z","timestamp":1772556414977,"version":"3.50.1"},"reference-count":0,"publisher":"International Association of Online Engineering (IAOE)","issue":"1","license":[{"start":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T00:00:00Z","timestamp":1772496000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Eng. Ped."],"abstract":"<jats:p>Soft skills development remains a critical challenge in higher education, especially in large, multidisciplinary learning environments where students vary in background, motivation, and self-regulatory capacity. Although problem-based learning (PBL) is broadly acknowledged as a successful method for developing critical skills and abilities such as planning, collaboration, and reflective thinking, traditional implementations often face constraints in personalization, coordination, and formative assessment. This study introduces an enhanced PBL model augmented by artificial intelligence (AI) Agents to support soft skills acquisition in blended learning contexts. The AI Agent, leveraging natural language processing (NLP) and automation via the n8n platform, functioned as a virtual assistant to facilitate task planning, peer coordination, self-monitoring, and timely feedback. A quasi-experimental study was carried out involving three groups of students (N = 263) participating in a course focused on developing soft skills, comprising one group using AI-supported PBL, another group using traditional PBL, and a control group taught through standard instructional methods. A mixed-methods analysis demonstrated that the group utilizing AI support exhibited statistically notable enhancements in their outcomes across six soft skill domains, particularly in planning, group work, and reflective learning (p &lt; 0.001). Behavioral data from LMS logs and product assessments further validated enhanced collaboration, consistency, and accuracy in self-assessment among AI-supported learners. The findings demonstrate that integrating AI Agents into PBL not only reduces instructor workload and enhances instructional equity but also empowers learners through personalized, data-driven scaffolding. This approach offers promising implications for scalable, technology-enhanced soft skills education across disciplines.<\/jats:p>","DOI":"10.3991\/ijep.v16i1.57581","type":"journal-article","created":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T14:33:27Z","timestamp":1772548407000},"source":"Crossref","is-referenced-by-count":0,"title":["Personalized and Scalable Problem-Based Learning in Soft Skills Education: The Role of AI Agents in Multidisciplinary Contexts"],"prefix":"10.3991","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0289-5883","authenticated-orcid":false,"given":"Dinh-Minh","family":"Vu","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3815-6380","authenticated-orcid":false,"given":"Hieu Hoc","family":"Le","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9592-0226","authenticated-orcid":false,"given":"Xuan Tan","family":"Phan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4564-1579","authenticated-orcid":false,"given":"Thi Thanh Tu","family":"Nguyen","sequence":"additional","affiliation":[]}],"member":"2371","published-online":{"date-parts":[[2026,3,3]]},"container-title":["International Journal of Engineering Pedagogy (iJEP)"],"original-title":[],"link":[{"URL":"https:\/\/online-journals.org\/index.php\/i-jep\/article\/download\/57581\/17043","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/online-journals.org\/index.php\/i-jep\/article\/download\/57581\/17043","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T14:33:27Z","timestamp":1772548407000},"score":1,"resource":{"primary":{"URL":"https:\/\/online-journals.org\/index.php\/i-jep\/article\/view\/57581"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,3]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,3,3]]}},"URL":"https:\/\/doi.org\/10.3991\/ijep.v16i1.57581","relation":{},"ISSN":["2192-4880"],"issn-type":[{"value":"2192-4880","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,3]]}}}